Evidence map›Paper›PMID 42807326›Full record

ArticleOxford open digital health2026

Maintenance dynamics in digital health public goods: a quasi-experimental study of issue resolution during the 2025 USAID funding disruption.

Jinyou Sheng, Amy Finnegan

Abstract read
In one paragraph

Article in Oxford open digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jinyou ShengDuke Global Health Institute, Duke University, Trent Hall, 310 Trent Drive, Durham, NC, 27710, United States.ORCID https://orcid.org/0009-0001-9207-6971
Amy FinneganDuke Global Health Institute, Duke University, Trent Hall, 310 Trent Drive, Durham, NC, 27710, United States.ORCID https://orcid.org/0000-0003-4940-6581

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Open-source digital public goods play a growing role in point-of-care health service delivery in low- and middle-income countries. Many of these systems are developed and maintained by organizations that rely heavily on donor funding, making their long-term sustainability vulnerable to funding instability. The January 2025 U.S. Agency for International Development funding freeze created a rare natural experiment to observe how different organizations maintaining these systems respond under external funding shocks. Using 7922 issues from eight repositories created between June 2023 and June 2025, a DistilBERT model was fine-tuned to classify bug severity. Organizations were categorized into three funding-based models: donor-driven (primarily grant-funded), revenue-driven (sustained through commercial or internal investment), and hybrid (combining grants and revenue). Interrupted time series and Cox proportional hazards models were then applied to evaluate changes in bug-resolution efficiency. Revenue-driven organizations did not exhibit a statistically significant immediate level change but experienced significant deterioration in the post-intervention period. Donor-driven organizations exhibited no substantial changes following the intervention, maintaining stable baseline levels. Hybrid organizations showed resilience to the immediate funding shock, with a gradual decline in bug resolution as time went on after the shock. These findings suggest that the funding shocks function as a stress test for digital public goods and highlight the resilience advantages of various governance models.

Indexed as

bug resolution efficiencydigital health public goodsfunding shocksopen-source software sustainabilityorganizational resilience

Identifiers

PMID42807326
PMCPMC13617568

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.